Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 643 585 51 962 849 850 817 222 334 681 141 623 337 357 667 14 990 944 417 626
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 334 643 623 626 14 NA 962 141 585 681 357 51 337 849 990 817 667 NA 944 417 850 222 NA
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 3 2 4 3 2 4 2 3 3 1
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "m" "r" "z" "i" "n" "R" "Y" "C" "X" "G"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 4 17 18
which( manyNumbersWithNA > 900 )
[1] 7 15 19
which( is.na( manyNumbersWithNA ) )
[1] 6 18 23
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 962 990 944
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 962 990 944
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 962 990 944
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "R" "Y" "C" "X" "G"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "m" "r" "z" "i" "n"
manyNumbers %in% 300:600
[1] FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE
[18] FALSE TRUE FALSE
which( manyNumbers %in% 300:600 )
[1] 2 9 13 14 19
sum( manyNumbers %in% 300:600 )
[1] 5
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "large" "large" "large" "small" NA "large" "small" "large" "large" "small" "small" "small"
[14] "large" "large" "large" "large" NA "large" "small" "large" "small" NA
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "large" "large" "large" "small" "UNKNOWN" "large" "small" "large" "large"
[11] "small" "small" "small" "large" "large" "large" "large" "UNKNOWN" "large" "small"
[21] "large" "small" "UNKNOWN"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 643 623 626 0 NA 962 0 585 681 0 0 0 849 990 817 667 NA 944 0 850 0 NA
unique( duplicatedNumbers )
[1] 3 2 4 1
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 3 2 4 1
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
which.max( manyNumbersWithNA )
[1] 15
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 990
which.min( manyNumbersWithNA )
[1] 5
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 14
range( manyNumbersWithNA, na.rm = TRUE )
[1] 14 990
manyNumbersWithNA
[1] 334 643 623 626 14 NA 962 141 585 681 357 51 337 849 990 817 667 NA 944 417 850 222 NA
sort( manyNumbersWithNA )
[1] 14 51 141 222 334 337 357 417 585 623 626 643 667 681 817 849 850 944 962 990
sort( manyNumbersWithNA, na.last = TRUE )
[1] 14 51 141 222 334 337 357 417 585 623 626 643 667 681 817 849 850 944 962 990 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 990 962 944 850 849 817 681 667 643 626 623 585 417 357 337 334 222 141 51 14 NA NA NA
manyNumbersWithNA[1:5]
[1] 334 643 623 626 14
order( manyNumbersWithNA[1:5] )
[1] 5 1 3 4 2
rank( manyNumbersWithNA[1:5] )
[1] 2 5 3 4 1
sort( mixedLetters )
[1] "C" "G" "i" "m" "n" "r" "R" "X" "Y" "z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 2.5 1.0 9.5 7.5 6.0 4.5 9.5 7.5 2.5 4.5
rank( manyDuplicates, ties.method = "min" )
[1] 2 1 9 7 6 4 9 7 2 4
rank( manyDuplicates, ties.method = "random" )
[1] 2 1 9 8 6 5 10 7 3 4
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 0.4282621 -1.2044679 0.4746821 1.7156764
[10] -1.6348784 2.6231200 0.5769743 0.5119942 -2.1176779 -0.4671653
round( v, 0 )
[1] -1 0 0 0 1 0 -1 0 2 -2 3 1 1 -2 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.4 -1.2 0.5 1.7 -1.6 2.6 0.6 0.5 -2.1 -0.5
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.43 -1.20 0.47 1.72 -1.63 2.62 0.58 0.51 -2.12 -0.47
floor( v )
[1] -1 -1 0 0 1 0 -2 0 1 -2 2 0 0 -3 -1
ceiling( v )
[1] -1 0 0 1 1 1 -1 1 2 -1 3 1 1 -2 0
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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